csranks 1.2.2
csranks 1.2.1
- Added new datasets,
pisa2018
and pisa2022
- Updated CITATION and references
- Bugfix of
plot.csranks
with non default indices
csranks 1.2.0
- Public release with contents of 1.1 (Rank-rank linear regression)
- Added a new mode for regression with clustered (grouped) data
- Bugfixes, doc, new vignette
csranks 1.1.1
- Optimized
vcov.lmranks
method
csranks 1.1.0
- Added
lmranks
function for linear modelling of ranks using single rank covariate and possibly other, “usual” covariates
- Implemented methods
print
, summary
, vcov
, confint
, predict
for lmranks
output
- Disabled a number of methods defined for
ļm
(like sigma
, AIC
or influence
)
csranks 1.0.0
- Release!
irank
now raises error if NAs present and na.rm
=FALSE
csranks 0.5.0
csranks
now produces csranks
object. List as before, but with new rank
element
- Added
plot.ranking
function
csranks 0.4.1
V
argument (sd
before 0.4) renamed to Sigma
- Adding
irank
and frank
functions
csranks 0.4.0
sd
argument renamed to V
; now accepts ONLY covariance matrix.
*_marg
and *_simul
methods removed; use *
with simul
option.
csranks 0.3.0
- Added possibility of features to be correlated across populations.
sd
argument now can accept covariance matrix.
csranks 0.2.0
- Added implementation of confidence sets for ranks based on multinomial data.
- Added implementation of confidence sets for tau-best and tau-worst.
csranks 0.1.0
- This is the first release of csranks.